“What happens to the SaaS markets when the cost of code approaches zero?” … “Few people truly grasp how hard bringing a software product to market is.”
Are these related? The difficulty of bringing a software product to market has never been that it takes time to produce code. We’ve had the concept of MVPs for decades and pre-AI companies have raised hundreds of millions off of no code prototypes.
YC has always preached that you launch. Launch today. Launch as soon as is humanly possible. And learn. And iterate. You get something into the market as soon as possible. Spending years building the perfect software has never been the strategy pursued by technology startups, and not because of the time it takes, but because you need users to know what to build.
I think we could even go as far as to counter your argument. We know that constraints are powerful. Constraints force us to focus. Imagine you decide to build an ATS. You spend a bunch of money on Claude Code to generate hundreds of features, every little idea you can think of, you include it. You launch with the most complete ATS on the market. Ashby can’t hold a candle to the depth of your software. Do you have a better chance of success than if you had launched with a much smaller surface area, experimented, found the right area of focus, and iterated according to user behavior?
I encounter a lot of vibe coded software products that people are launching and I am not precious about code, a good product is a good product whether it was hand crafted over a decade by a thousand well paid programmers or generated in an afternoon by Claude Code from a laypersons prompt. I can name one single vibe coded product I pay for that is genuinely good software. All that the AI age has done is show that most of us absolutely suck at building products, and that even with free code, what we produce is garbage.
“How could the market afford to build and sustain each offering?”
I think you’re conflating build and sustain here. Nothing fundamental about business has changed. Sustaining a business isn’t about being able to generate code. Even in a world where code is free, how could the market sustain 10,000 Ashbys? Where are the customers coming from?
As a concrete example: how many customers does Jira have despite Linear being better software in every single way? Would generating 1,000 more Linears change Jira’s market position? Or Microsoft Teams, Teams is awful, there are so many better options. Will generating 1,000 more better options change Microsoft Teams’s position?
The P&L of every software company has an R&D expense (R) in a total cost (T). We can debate what R is, and R might be approaching 0, but it is not 0.
This does not mean that R is on the only cost (T-R grows over the life of the company). It does not mean that, even if R were 0, you could launch a product. But R is a real cost.
“I do believe that cost of producing code is approaching to zero, and that means hundreds or even thousands of offerings will exist in every shape, way and form we can imagine.”
What proportion of T does R need to be to see thousands of Ashbys appear?
Ashby is a good example to discuss because it is serious software for serious businesses, it isn’t a calorie counting app. Serious business expects so much more out of their suppliers than software, Ashby is so much more than a bunch of code.
So, a thousand people generate their own ashbys, then what? Are companies like Shopify and Ramp going to trust their ATS to some person who generated some software in a day?
I agree that the cost of building software has gone down a lot and that lowers the barrier to entry for building a software business. I completely disagree that the market could support even 10x the number of companies in each vertical, let alone 100x or 1000x.
You could clone Ashby today and go to Ramp and offer them a 50% discount on whatever they’re paying Ashby and there is zero chance you win their business. You could clone Ashby and the add 10x the features and go to ramp and offer a 75% discount and there is zero chance of you winning their business.
The subscriptions are not available to enterprise users. Enterprise users must pay per-token. A $200 subscription gives you roughly the equivalent of $1500 in per-token billing.
What does enterprise mean in this context? Is it about privacy guarantees not offfered for the subscriptions? For sensitive data the only solution is local. But maybe companies do trust these agreements? I'm very confused.
Simon is very fascinated by AI and at times he can be a little too optimistic but he is generally balanced and his perspective evolves over time which can be seen in his writing.
Nerd who loves nerd things a little too much? Sure. Paid shill by Big LLM? Nah.
Literally none of those articles are critizing LLMs, only use made of them by 3rd party actors outside of the providers. It really has nothing to do with LLMs themselves.
The fact that you had to dig to August 2025 to find a single article that's actually a critic of something produced by the AI labs is just further proof.
The prompt injection stuff is very critical of both the technology and the LLM providers especially when I call out that their solution is still to say "they're getting better at avoiding the attacks" when my line has consistently been that "99% is a failing grade".
As someone involved in the WebExtensions Community Group who has been (slowly) trying to figure out what, if anything, we should do at the platform level around these use cases, I appreciate you raising and repeating this concern. I'd be obliged if you have any other recommended reading around this topic.
“I'm finding that coding agents can take me from a vague idea to a working solution, one with tests and documentation and that looks like a carefully considered project evolved over the course of many weeks... in less than an hour.
Even if the code is rock solid, there's a limit to how many projects like that I can sensibly care for - and if they're instantly abandoned, what value was there from creating them in the first place?”
Here is Simon questioning a fundamental belief held by the pro-LLM lobby. Would a paid shill question that?
Simon is, without question, an enthusiastic pro-LLM person. I disagree with what he says often, the product market fit post was a bad take. But I don’t believe he is shying away from sharing his thoughts when they’re not favorable to the industry.
That's not at all negative about LLMs, just negative about his own usage of LLMs. He's still very heavily and unrealistically (unless he has very poor coding standards and skills, which I won't rule out) praising LLMs in the sentences you've quoted.
Note that it's not surprising that he finds his own usage (described in the quote) negative, since his real job is as a blogger, not anything else.
No, we know from the financials of these companies that API prices are close to being at cost and the individual developer plans are heavily subsidized (because they are roughly 10% of API cost per token[1]).
If plans were at cost and API pricing was marked up that would mean there’s a 90%+ profit margin on tokens and instead of raising money and talking about revenue, Anthropic and OpenAI would be talking about their obscene profits.
[1] the caveat is that the average plan user probably doesn’t use all of their quota, I guess maybe 30% is the average across all users.
That’s a very simplified view of HR. Human Resources does a lot of things. During the cash rich days a tech company HR department might end up doing a bunch of nonsense[1] but the fundamental value of the department is there and will continue.
HR is rarely involved in hiring decisions, that’s the responsibility of the hiring manager which is typically the new hire’s manager. At a very big company you might have HR screening applicants but that’s to save time for hiring managers.
[1] just as engineering ends up doing a bunch of nonsense when the money is flowing.
As people in tech we live very expensive lives but if you are in a major city and own your own home and have worked for a decade or more you probably have a lot more opportunity to retire today than you might think. Even with children, life can be much less expensive by moving to a low cost of living area. Often in online discussions about FIRE (Financial Independence, Retire Early) high income people will discuss needing many millions to retire, but you can retire on less.
Switching industries is a romantic idea but it is very difficult, especially going from the tech world with big money to the normal world with small money. You can still work to keep yourself busy but thinking about it as retirement will better help you plan. Going part time in tech is usually more sustainable than trying to switch industries.
A good place to start is thinking about what you want from life without work. Where do you want to be? Where does your partner and your kids want to be? What do they want out of life? From there you can assess the financial needs and plan accordingly.
The race is pretty much designed to be a difficult for horses as possible to give humans a chance. Except for the parts that are extremely difficult for horses, horses steamroll the human competitors.
I’m confused by the confusion. Groq licensed their technology (sold part of their business) to Nvidia for a large amount of money and distributed the spoils to their investors. Seems quite normal? But then the Axios article says…
“Existing shareholders will receive the remaining cash distributions and then have the opportunity to invest into a new company”
New company? But Groq still exists and continued to exist.
“The bottom line: Don't be surprised if this becomes a new transaction template in the AI private markets.”
A transaction template? I don’t follow what was novel about this situation. The Meta not-acquisition-acquisition of Scale seems more novel.
I guess I feel like Zach’s confusion is because of the way Axios has presented what is happening to Groq. Looking at why actually happened with Groq, it seems like Axios are reporting it weird.
Unless Groq really is starting a new company in which case I am equally as confused.
The interesting thing here isn't "how, logistically, is the Groq corporate entity able to raise more money?". That's straightforward.
Rather, the interesting thing and the topic of most of the article is "how, after Nvidia hired most of Groq's team and licensed all their IP, did Groq manage to convince investors to invest in the remaining corporate entity?"
There's nothing normal at all about the Nvidia Groq deal, it's hard to read in terms of what it means. A straight licensing deal would have been easier to ingest.
I could be completely off the mark but I thought the non-exclusive license was necessary because Groq’s datacenter business uses the technology already? Nvidia acquired the assets but Groq needed to retain rights to use the technology for their own product.
Are these related? The difficulty of bringing a software product to market has never been that it takes time to produce code. We’ve had the concept of MVPs for decades and pre-AI companies have raised hundreds of millions off of no code prototypes.
YC has always preached that you launch. Launch today. Launch as soon as is humanly possible. And learn. And iterate. You get something into the market as soon as possible. Spending years building the perfect software has never been the strategy pursued by technology startups, and not because of the time it takes, but because you need users to know what to build.
I think we could even go as far as to counter your argument. We know that constraints are powerful. Constraints force us to focus. Imagine you decide to build an ATS. You spend a bunch of money on Claude Code to generate hundreds of features, every little idea you can think of, you include it. You launch with the most complete ATS on the market. Ashby can’t hold a candle to the depth of your software. Do you have a better chance of success than if you had launched with a much smaller surface area, experimented, found the right area of focus, and iterated according to user behavior?
I encounter a lot of vibe coded software products that people are launching and I am not precious about code, a good product is a good product whether it was hand crafted over a decade by a thousand well paid programmers or generated in an afternoon by Claude Code from a laypersons prompt. I can name one single vibe coded product I pay for that is genuinely good software. All that the AI age has done is show that most of us absolutely suck at building products, and that even with free code, what we produce is garbage.
“How could the market afford to build and sustain each offering?”
I think you’re conflating build and sustain here. Nothing fundamental about business has changed. Sustaining a business isn’t about being able to generate code. Even in a world where code is free, how could the market sustain 10,000 Ashbys? Where are the customers coming from?
As a concrete example: how many customers does Jira have despite Linear being better software in every single way? Would generating 1,000 more Linears change Jira’s market position? Or Microsoft Teams, Teams is awful, there are so many better options. Will generating 1,000 more better options change Microsoft Teams’s position?